Response to the DOD RFI on Defense Industrial Base Adoption of Artificial Intelligence for Defense Applications
IAPS submitted a response to a Department of Defense Request for Information on Defense Industrial Base Adoption of AI for Defense Applications.
Mapping Technical Safety Research at AI Companies
This report analyzes the research published by Anthropic, Google DeepMind, and OpenAI about safe AI development, as well as corporate incentives to research different areas. This research reveals where corporate attention is concentrated and where there are potential gaps.
The Future of International Scientific Assessments of AI’s Risks
This piece is a link post for a paper which was led by Hadrien Pouget (Carnegie Endowment for International Peace) and Claire Dennis (Centre for the Governance of AI). IAPS staff Renan Araujo and Oliver Guest were among the paper’s co-authors.
Assuring Growth: Making the UK a Global Leader in AI Assurance Technology
This policy memo by Jam Kraprayoon and Bill Anderson-Samways, published by the UKDayOne and the Social Market Foundation, recommends that the UK government implement a targeted market-shaping program mobilizing public and private sector investment to supercharge the UK’s AI assurance technology industry.
An Early Warning System For AI-Powered Threats To National Security And Public Safety
This policy memo by Jam Kraprayoon, Joe O’Brien, and Shaun Ee (IAPS), published by the Federation of American Scientists, proposes that Congress should set up an early warning system for novel AI-enabled threats to provide defenders maximal time to respond to a given capability before information about it is disclosed or leaked to the public.
Coordinated Disclosure of Dual-Use Capabilities: An Early Warning System for Advanced AI
Future AI systems may be capable of enabling offensive cyber operations, lowering the barrier to entry for designing and synthesizing bioweapons, and other high-consequence dual-use applications. If and when these capabilities are discovered, who should know first, and how? We describe a process for information-sharing on dual-use capabilities and make recommendations for governments and industry to develop this process.
Are Consumer GPUs a Problem for US Export Controls?
This report analyzes the potential impact of high-end consumer GPUs on the efficacy of US export controls on AI chips. It studies three stockpiling scenarios and what AI capabilities those may enable, and makes recommendations for policymakers.
Spreadsheets vs. Smugglers: Modernizing the BIS for an Era of Tech Rivalry
This blog post by Erich Grunewald (IAPS) and Samuel Hammond (the Foundation for American Innovation) argues that Congress should increase the funding of the Bureau of Industry and Security.
Topics for Track IIs: What Can Be Discussed in Dialogues About Advanced AI Risks Without Leaking Sensitive Information?
This issue brief suggests agenda items for dialogues about advanced AI risks that minimize risk of leaking sensitive information.
Highlights for Responsible AI from the Biden Administration's FY2025 Budget Proposal
This issue brief analyzes key AI-related allocations from the Biden FY2025 Presidential Budget in terms of their potential impact on the responsible development of advanced AI.
Responsible Reporting for Frontier AI Development
Mitigating the risks from frontier AI systems requires up-to-date and reliable information about those systems. Organizations that develop and deploy frontier systems have significant access to such information. By reporting safety-critical information to actors in government, industry, and civil society, these organizations could improve visibility into new and emerging risks posed by frontier systems.
AI-Relevant Regulatory Precedents: A Systematic Search Across All Federal Agencies
A systematic search for potential case studies relevant to advanced AI regulation in the United States, looking at all federal agencies for factors such as level of expertise, use of risk assessment, and analysis of uncertain phenomena.
Responsible Scaling: Comparing Government Guidance and Company Policy
This issue brief evaluates the original example of a Responsible Scaling Policy (RSP) – that of Anthropic – against guidance on responsible capability scaling from the UK Department for Science, Innovation and Technology (DSIT).
Response to the NIST RFI on Auditing, Evaluating, and Red-Teaming AI Systems
IAPS’s response to a NIST RFI, outlining specific guidelines and practices that could help AI actors better manage and mitigate risks from AI systems, particularly from dual-use foundation models.
Secure, Governable Chips
Today, the Center for a New American Security (CNAS), in collaboration with the Institute for AI Policy and Strategy, has released a new report, Secure, Governable Chips, by Onni Aarne, Tim Fist, and Caleb Withers.
The report introduces the concept of “on-chip governance,” detailing how security features on AI chips could help mitigate national security risks from the development of broadly capable dual-use AI systems, while protecting user privacy.
Catching Bugs: The Federal Select Agent Program and Lessons for AI Regulation
This paper examines the Federal Select Agent Program, the linchpin of US biosecurity regulations. It then draws out lessons for AI regulation regarding licensing, regulatory expertise, and the merits of “risk-based” vs. “list-based” systems.
Introduction to AI Chip Making in China
This primer introduces the topic of Chinese AI chip making, relevant to understanding and forecasting China's progress in producing AI chips indigenously.
Safeguarding the Safeguards: How Best to Promote Alignment in the Public Interest
With this paper, we aim to help actors who support alignment efforts to make these efforts as effective as possible, and to avoid potential adverse effects.
Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework
This paper discusses how external scrutiny (such as third-party auditing, red-teaming, and researcher access) can bring public accountability to bear on decisions regarding the development and deployment of frontier AI models.
Preventing AI Chip Smuggling to China
We link to a working paper which was led by Tim Fist of the Center for a New American Security, and coauthored with IAPS researcher Erich Grunewald. It builds on IAPS's earlier report on AI chip smuggling into China.